Explore the vast range of titles available.

This article focuses on dynamic signatures and their features. It provides a detailed and critical review of dynamic feature variations and circumstantial parameters affecting dynamic signatures. The state of the art summarizes available knowledge, meant to assist the forensic practitioner in cases presenting extraordinary writing conditions. The studied parameters include hardware-related issues, aging and the influence of time, as well as physical and mental states of the writer. Some parameters, such as drug and alcohol abuse or medication, have very strong effects on handwriting and signature dynamics. Other conditions such as the writer’s posture and fatigue have been found to affect feature variation less severely. The need for further research about the influence of these parameters, as well as handwriting dynamics in general is highlighted. These factors are relevant to the examiner in the assessment of the probative value of the reported features. Additionally, methodology for forensic examination of dynamic signatures is discussed. Available methodology and procedures are reviewed, while pointing out major technical and methodological advances in the field of forensic handwriting examination. The need for sharing the best practice manuals, standard operating procedures and methodologies to favor further progress is accentuated.

Friedreich’s ataxia (FRDA) is an autosomal-recessive neurodegenerative and cardiac disorder which occurs when transcription of the FXN gene is silenced due to an excessive expansion of GAA repeats into its first intron. Herein, we generate dorsal root ganglia organoids (DRG organoids) by in vitro differentiation of human iPSCs. Bulk and single-cell RNA sequencing show that DRG organoids present a transcriptional signature similar to native DRGs and display the main peripheral sensory neuronal and glial cell subtypes. Furthermore, when co-cultured with human intrafusal muscle fibers, DRG organoid sensory neurons contact their peripheral targets and reconstitute the muscle spindle proprioceptive receptors. FRDA DRG organoids model some molecular and cellular deficits of the disease that are rescued when the entire FXN intron 1 is removed, and not with the excision of the expanded GAA tract. These results strongly suggest that removal of the repressed chromatin flanking the GAA tract might contribute to rescue FXN total expression and fully revert the pathological hallmarks of FRDA DRG neurons. Friedreich’s ataxia (FRDA) is an autosomal-recessive disorder. Here the authors describe a DRG organoid from patient derived-neurons and co-culture with muscle cells to mimic the disorder in vitro and demonstrate potential correction of the phenotype by CRISPR based editing.

•Methodic investigation of a probabilistic evidence evaluation methodology.•Application of a probabilistic model allowing use of empirical data for evidence evaluation.•Insights on dealing with data sparsity, different signature styles and combining features.•Preliminary study on 3 dynamic signatures, with high reproducibility and transparency. Forensic handwriting examiners (FHE) activities are focused on comparative analysis of handwritten objects such as signatures. Their role is to provide and evaluate evidence for and against the authenticity of a questioned signature. In recent years, cases involving handwritten signatures captured on electronic devices have become more commonplace. These so-called ‘dynamic signatures’ (also known as ‘digitally captured signatures’) are much different from paper-based signatures. Not only does the medium of recording differ, but also the type, volume of data and features are different from the pattern-based evidence that makes up paper-based signatures. Recent developments in forensic science – including signature examination – have led to the adoption of evaluative probabilistic methodologies in many disciplines [see, e.g. ENFSI 1915 Guidelines]. In the current paper, a probabilistic model to evaluate signature evidence in the form of multivariate data, as proposed and described in Wacom Europe GmbH (2019), is adopted. Topics like data sparsity, joint evaluation of multiple features and feature selection are investigated. Performed experimental studies showed an accuracy rate above 90% even when a limited number (5) of reference signatures was available. The performances of a multivariate approach are compared with those characterizing a so-called multiplicative approach where variables (features) are taken as independent and the Bayes’ factor (BF) is obtained as the product of univariate BFs associated to each selected feature. The simplicity of this latter approach is, however, accompanied by severe issues about the reliability of results. The use of a multivariate approach is therefore highly recommended. Finally, the evidential values in correspondence of alternative feature sets are compared. Results suggest that discriminative features are writer-related and necessitate a case-specific selection.

A question of originality was raised concerning the authorship of Molière’s plays. It has been claimed that the plays were written by Corneille in the final part of his life. This controversy is still topical, despite the relevant contributions on the subject (e.g., 1 ). Stylometry is often invoked to identify patterns used within and between words and sentences that describe a personal way of writing texts, and so one’s style. Despite the pioneering contribution of 2 , who promoted a Bayesian procedure for assessing the authorship of disputed documents, a coherent and judicially sound approach for features assessment and authorship attribution is still lacking in current practice. A full Bayesian framework to deal with the questioned authorship of the selected plays is promoted to address this controversy in total respect of (a) international standards for evaluative reporting in forensic science and (b) legal jurisprudence. Results strongly support the hypothesis that Corneille did not write Molière’s literary plays.

Key Points Humans are afflicted by two forms of hereditary ataxia, autosomal recessive and autosomal dominant. Neurological dysfunction associated with these disorders impairs motor coordination. Mutated proteins associated with autosomal recessive ataxias compromise the regulation of energy output, oxidative stress, DNA maintenance and the cell cycle. Diseases of this type include Friedreich ataxia, Cayman ataxia, ataxia telangiectasia and abetalipoproteinaemia. Friedreich ataxia is the most common hereditary ataxia. Mutation of the mitochondrial protein frataxin causes this disorder, probably by perturbing mitochondrial iron metabolism and the cellular response to oxidative stress. The second most prevalent form of ataxia is the genomic instability syndrome ataxia telangiectasia. The gene that is mutated in this disorder, ATM , encodes a protein that coordinates cellular responses to DNA damage. Autosomal dominant spinocerebellar ataxias are caused by expanded CAG-triplet repeats in the respective disease genes. The encoded mutant ataxin proteins have abnormally long polyglutamine stretches, leading to toxic gain-of-function. Protein aggregates are hallmarks of neurodegeneration in the brains of patients with spinocerebellar ataxia, but a direct link between these aggregates and neuronal death has yet to be confirmed. There is evidence that perturbed gene transcription might also contribute to neurodegeneration. Two groups of hereditary ataxias are most relevant to humans — the autosomal recessive ataxias and the autosomal dominant spinocerebellar ataxias. Recessive ataxias are multisystem disorders that are characterized by inactivating mutations that result in loss of protein function. By contrast, cell death associated with dominant spinocerebellar ataxias is mostly restricted to the CNS, and cellular control of protein folding and processing is affected. The purpose of this review is to provide an integrated view of the field, encompassing the similarities — which are few — and the differences — which are many — between pathological processes that cause ataxia. In reviewing the current knowledge of ataxias, we discuss recent insights into the pathogenic mechanisms that lead to specific neuronal dysfunction and neurodegeneration.

The academic and scientific world in general is increasingly concerned about their inability to determine and ascertain the identity of the writer of a text. More and more often the question arises as to whether a scientific article or work handed in by a student was actually produced by the alleged author of the questioned text. The role of artificial intelligence (AI) is increasingly debated due to its dangers of undeclared use. A current example is undoubtedly the undeclared use of ChatGPT to write a scientific text. The article promotes an AI model-independent redundancy measure to support discrimination between hypotheses on authorship of various multilingual texts written by humans or produced by intelligence media such as ChatGPT. The syntax of texts written by humans tends to differ from that of texts produced by AIs. This difference can be grasped and quantified even with short texts (i.e. 1800 characters). This aspect of length is extremely important, because short texts imply a greater difficulty of analysis to characterize authorship. To meet the efficiency criteria required for the evaluation of forensic evidence, a probabilistic approach is implemented. In particular, to assess the value of the redundancy measure and to offer a consistent classification criterion, a metric called Bayes factor is implemented. The proposed Bayesian probabilistic method represents an original approach in stylometry. Analyses performed over multilingual texts (English and French) covering different scientific and human areas of interest (forensic science and socio-psycho-artistic topics) reveal the feasibility of a successful authorship discrimination with limited misclassification rates. Model performance is satisfactory even with small sample sizes.

\"This book should have a place on the bookshelf of every forensic scientist who cares about the science of evidence interpretation\"Dr. Ian Evett, Principal Forensic Services Ltd, London, UKContinuing developments in science and technology mean that the amounts of information forensic scientists are able to provide for criminal investigations is ever increasing.The commensurate increase in complexity creates difficulties for scientists and lawyers with regard to evaluation and interpretation, notably with respect to issues of inference and decision.Probability theory, implemented through graphical methods, and specifically Bayesian networks, provides powerful methods to deal with this complexity. Extensions of these methods to elements of decision theory provide further support and assistance to the judicial system.Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science provides a unique and comprehensive introduction to the use of Bayesian decision networks for the evaluation and interpretation of scientific findings in forensic science, and for the support of decision-makers in their scientific and legal tasks.Includes self-contained introductions to probability and decision theory.Develops the characteristics of Bayesian networks, object-oriented Bayesian networks and their extension to decision models.Features implementation of the methodology with reference to commercial and academically available software.Presents standard networks and their extensions that can be easily implemented and that can assist in the reader's own analysis of real cases.Provides a technique for structuring problems and organizing data based on methods and principles of scientific reasoning.Contains a method for the construction of coherent and defensible arguments for the analysis and evaluation of scientific findings and for decisions based on them.Is written in a lucid style, suitable for forensic scientists and lawyers with minimal mathematical background.Includes a foreword by Ian Evett.The clear and accessible style of this second edition makes this book ideal for all forensic scientists, applied statisticians and graduate students wishing to evaluate forensic findings from the perspective of probability and decision analysis. It will also appeal to lawyers and other scientists and professionals interested in the evaluation and interpretation of forensic findings, including decision making based on scientific information.

Franco Taroni and colleagues report the identification of mutations in AFG3L2 that cause dominant spinocerebellar ataxia type 28. Along with paraplegin, AFG3L2 forms a protein complex with ATPase and metalloprotease activities and functions in the maintenance of the mitochondrial proteome. Autosomal dominant spinocerebellar ataxias (SCAs) are genetically heterogeneous neurological disorders characterized by cerebellar dysfunction mostly due to Purkinje cell degeneration. Here we show that AFG3L2 mutations cause SCA type 28. Along with paraplegin, which causes recessive spastic paraplegia, AFG3L2 is a component of the conserved m -AAA metalloprotease complex involved in the maintenance of the mitochondrial proteome. We identified heterozygous missense mutations in five unrelated SCA families and found that AFG3L2 is highly and selectively expressed in human cerebellar Purkinje cells. m -AAA–deficient yeast cells expressing human mutated AFG3L2 homocomplex show respiratory deficiency, proteolytic impairment and deficiency of respiratory chain complex IV. Structure homology modeling indicates that the mutations may affect AFG3L2 substrate handling. This work identifies AFG3L2 as a novel cause of dominant neurodegenerative disease and indicates a previously unknown role for this component of the mitochondrial protein quality control machinery in protecting the human cerebellum against neurodegeneration.

The leading resource in the statistical evaluation and interpretation of forensic evidence  The third edition of Statistics and the Evaluation of Evidence for Forensic Scientists is fully updated to provide the latest research and developments in the use of statistical techniques to evaluate and interpret evidence. Courts are increasingly aware of the importance of proper evidence assessment when there is an element of uncertainty. Because of the increasing availability of data, the role of statistical and probabilistic reasoning is?gaining a higher profile in criminal cases. That's why lawyers, forensic scientists, graduate students, and researchers will find this book an essential resource, one which explores how forensic evidence can be evaluated and interpreted statistically. It's written as an accessible source of information for all those with an interest in the evaluation and interpretation of forensic scientific evidence.     Discusses the entire chain of reasoning-from evidence pre-assessment to court presentation;  Includes material for the understanding of evidence interpretation for single and multiple trace evidence;  Provides real examples and data for improved understanding.  Since the first edition of this book was published in 1995, this respected series has remained a leading resource in the statistical evaluation of forensic evidence. It shares knowledge from authors in the fields of statistics and forensic science who are international experts in the area of evidence evaluation and interpretation. This book helps?people to deal with uncertainty related to scientific evidence and propositions. It?introduces?a?method of reasoning that shows?how to?update beliefs coherently and to?act rationally.?In this edition, readers can find new information on the topics of elicitation, subjective probabilities, decision analysis, and cognitive bias, all discussed in a Bayesian framework.  

BackgroundInherited peripheral neuropathies (IPNs) represent a broad group of genetically and clinically heterogeneous disorders, including axonal Charcot-Marie-Tooth type 2 (CMT2) and hereditary motor neuropathy (HMN). Approximately 60%–70% of cases with HMN/CMT2 still remain without a genetic diagnosis. Interestingly, mutations in HMN/CMT2 genes may also be responsible for motor neuron disorders or other neuromuscular diseases, suggesting a broad phenotypic spectrum of clinically and genetically related conditions. Thus, it is of paramount importance to identify novel causative variants in HMN/CMT2 patients to better predict clinical outcome and progression.MethodsWe designed a collaborative study for the identification of variants responsible for HMN/CMT2. We collected 15 HMN/CMT2 families with evidence for autosomal recessive inheritance, who had tested negative for mutations in 94 known IPN genes, who underwent whole-exome sequencing (WES) analyses. Candidate genes identified by WES were sequenced in an additional cohort of 167 familial or sporadic HMN/CMT2 patients using next-generation sequencing (NGS) panel analysis.ResultsBioinformatic analyses led to the identification of novel or very rare variants in genes, which have not been previously associated with HMN/CMT2 (ARHGEF28, KBTBD13, AGRN and GNE); in genes previously associated with HMN/CMT2 but in combination with different clinical phenotypes (VRK1 and PNKP), and in the SIGMAR1 gene, which has been linked to HMN/CMT2 in only a few cases. These findings were further validated by Sanger sequencing, segregation analyses and functional studies.ConclusionsThese results demonstrate the broad spectrum of clinical phenotypes that can be associated with a specific disease gene, as well as the complexity of the pathogenesis of neuromuscular disorders.